Data Science/Machine Learning Director

AlixPartners - Southfield, MI

Full-time - Senior

Southfield, MI

Professional, Scientific, and Technical Services

About the position

The Data Science/Machine Learning Director at AlixPartners is responsible for leading data-driven initiatives that address complex challenges faced by clients. This role involves working closely with senior leadership, including owners and CEOs, to develop and implement data strategies that drive measurable improvements in performance. The director will oversee the creation of ETL workflows, statistical models, and visualizations, ensuring the integrity and usability of data across various systems.

Responsibilities

• Create ETL workflows, scripts, statistical models, and visualizations.
• Design, build, test, execute, and support data migration and cleansing processes.
• Select features and build classifiers using machine learning techniques.
• Execute machine learning projects using state-of-the-art methods.
• Extend company's data with third-party sources when needed.
• Create automated anomaly detection systems and track their performance.
• Collect data from various corporate databases and formats.
• Parse data from poorly structured XML and invalid HTML documents.
• Automate repetitive tasks with scripts.
• Build effective ETL processes for data ingestion flow.
• Design database models and advanced dimensional schemas.
• Apply business intelligence patterns and data management techniques.
• Demonstrate advanced SQL skills to work with extensive data.
• Review and analyze legacy code/scripts to understand data processing logic.

Requirements

• Extensive experience in data science and machine learning.
• Proficiency in Python, PySpark, or R, with excellence in at least one.
• Strong understanding of machine learning techniques and algorithms.
• Experience with SQL databases such as Microsoft, Redshift, Teradata, Oracle, and Netezza.
• Ability to parse and manipulate data from various formats and sources.
• Experience in building and optimizing classifiers using machine learning techniques.
• Understanding of cloud architectures, preferably Azure, AWS, or GCP.
• Advanced SQL skills, including CTEs and window functions.

Nice-to-haves

• Experience with data visualization tools.
• Familiarity with big data technologies.
• Knowledge of statistical learning languages for predictive modeling.

Benefits

• Health insurance coverage.
• 401k retirement savings plan.
• Flexible scheduling options.
• Professional development opportunities.